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<main>
<article id="content">
<header>
<h1 class="title"><code>simpleder.der</code> module</h1>
</header>
<section id="section-intro">
<details class="source">
<summary>Source code</summary>
<pre><code class="python">from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import numpy as np
from scipy import optimize


def check_input(hyp):
    &#34;&#34;&#34;Check whether a hypothesis/reference is valid.

    Args:
        hyp: a list of tuples, where each tuple is (speaker, start, end)
            of type (string, float, float)

    Raises:
        TypeError: if the type of `hyp` is incorrect
        ValueError: if some tuple has start &gt; end; or if two tuples intersect
            with each other
    &#34;&#34;&#34;
    if not isinstance(hyp, list):
        raise TypeError(&#34;Input must be a list.&#34;)
    for element in hyp:
        if not isinstance(element, tuple):
            raise TypeError(&#34;Input must be a list of tuples.&#34;)
        if len(element) != 3:
            raise TypeError(
                &#34;Each tuple must have the elements: (speaker, start, end).&#34;)
        if not isinstance(element[0], str):
            raise TypeError(&#34;Speaker must be a string.&#34;)
        if not isinstance(element[1], float) or not isinstance(
                element[2], float):
            raise TypeError(&#34;Start and end must be float numbers.&#34;)
        if element[1] &gt; element[2]:
            raise ValueError(&#34;Start must not be larger than end.&#34;)
    num_elements = len(hyp)
    for i in range(num_elements - 1):
        for j in range(i + 1, num_elements):
            if compute_intersection_length(hyp[i], hyp[j]) &gt; 0.0:
                raise ValueError(
                    &#34;Input must not contain overlapped speech.&#34;)


def compute_total_length(hyp):
    &#34;&#34;&#34;Compute total length of a hypothesis/reference.

    Args:
        hyp: a list of tuples, where each tuple is (speaker, start, end)
            of type (string, float, float)

    Returns:
        a float number for the total length
    &#34;&#34;&#34;
    total_length = 0.0
    for element in hyp:
        total_length += element[2] - element[1]
    return total_length


def compute_intersection_length(A, B):
    &#34;&#34;&#34;Compute the intersection length of two tuples.

    Args:
        A: a (speaker, start, end) tuple of type (string, float, float)
        B: a (speaker, start, end) tuple of type (string, float, float)

    Returns:
        a float number of the intersection between `A` and `B`
    &#34;&#34;&#34;
    max_start = max(A[1], B[1])
    min_end = min(A[2], B[2])
    return max(0.0, min_end - max_start)


def compute_merged_total_length(ref, hyp):
    &#34;&#34;&#34;Compute the total length of the union of reference and hypothesis.

    Args:
        ref: a list of tuples for the ground truth, where each tuple is
            (speaker, start, end) of type (string, float, float)
        hyp: a list of tuples for the diarization result hypothesis, same type
            as `ref`

    Returns:
        a float number for the union total length
    &#34;&#34;&#34;
    # Remove speaker label and merge.
    merged = [(element[1], element[2]) for element in (ref + hyp)]
    # Sort by start.
    merged = sorted(merged, key=lambda element: element[0])
    num_elements = len(merged)
    for i in reversed(range(num_elements - 1)):
        if merged[i][1] &gt;= merged[i + 1][0]:
            max_end = max(merged[i][1], merged[i + 1][1])
            merged[i] = (merged[i][0], max_end)
            del merged[i + 1]
    total_length = 0.0
    for element in merged:
        total_length += element[1] - element[0]
    return total_length


def build_speaker_index(hyp):
    &#34;&#34;&#34;Build the index for the speakers.

    Args:
        hyp: a list of tuples, where each tuple is (speaker, start, end)
            of type (string, float, float)

    Returns:
        a dict from speaker to integer
    &#34;&#34;&#34;
    speaker_set = sorted({element[0] for element in hyp})
    index = {speaker: i for i, speaker in enumerate(speaker_set)}
    return index


def build_cost_matrix(ref, hyp):
    &#34;&#34;&#34;Build the cost matrix.

    Args:
        ref: a list of tuples for the ground truth, where each tuple is
            (speaker, start, end) of type (string, float, float)
        hyp: a list of tuples for the diarization result hypothesis, same type
            as `ref`

    Returns:
        a 2-dim numpy array, whose element (i, j) is the overlap between
            `i`th reference speaker and `j`th hypothesis speaker
    &#34;&#34;&#34;
    ref_index = build_speaker_index(ref)
    hyp_index = build_speaker_index(hyp)
    cost_matrix = np.zeros((len(ref_index), len(hyp_index)))
    for ref_element in ref:
        for hyp_element in hyp:
            i = ref_index[ref_element[0]]
            j = hyp_index[hyp_element[0]]
            cost_matrix[i, j] += compute_intersection_length(
                ref_element, hyp_element)
    return cost_matrix


def DER(ref, hyp):
    &#34;&#34;&#34;Compute Diarization Error Rate.

    Args:
        ref: a list of tuples for the ground truth, where each tuple is
            (speaker, start, end) of type (string, float, float)
        hyp: a list of tuples for the diarization result hypothesis, same type
            as `ref`

    Returns:
        a float number for the Diarization Error Rate
    &#34;&#34;&#34;
    check_input(ref)
    check_input(hyp)
    ref_total_length = compute_total_length(ref)
    cost_matrix = build_cost_matrix(ref, hyp)
    row_index, col_index = optimize.linear_sum_assignment(-cost_matrix)
    optimal_match_overlap = cost_matrix[row_index, col_index].sum()
    union_total_length = compute_merged_total_length(ref, hyp)
    der = (union_total_length - optimal_match_overlap) / ref_total_length
    return der</code></pre>
</details>
</section>
<section>
</section>
<section>
</section>
<section>
<h2 class="section-title" id="header-functions">Functions</h2>
<dl>
<dt id="simpleder.der.DER"><code class="name flex">
<span>def <span class="ident">DER</span></span>(<span>ref, hyp)</span>
</code></dt>
<dd>
<section class="desc"><p>Compute Diarization Error Rate.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>ref</code></strong></dt>
<dd>a list of tuples for the ground truth, where each tuple is
(speaker, start, end) of type (string, float, float)</dd>
<dt><strong><code>hyp</code></strong></dt>
<dd>a list of tuples for the diarization result hypothesis, same type
as <code>ref</code></dd>
</dl>
<h2 id="returns">Returns</h2>
<p>a float number for the Diarization Error Rate</p></section>
<details class="source">
<summary>Source code</summary>
<pre><code class="python">def DER(ref, hyp):
    &#34;&#34;&#34;Compute Diarization Error Rate.

    Args:
        ref: a list of tuples for the ground truth, where each tuple is
            (speaker, start, end) of type (string, float, float)
        hyp: a list of tuples for the diarization result hypothesis, same type
            as `ref`

    Returns:
        a float number for the Diarization Error Rate
    &#34;&#34;&#34;
    check_input(ref)
    check_input(hyp)
    ref_total_length = compute_total_length(ref)
    cost_matrix = build_cost_matrix(ref, hyp)
    row_index, col_index = optimize.linear_sum_assignment(-cost_matrix)
    optimal_match_overlap = cost_matrix[row_index, col_index].sum()
    union_total_length = compute_merged_total_length(ref, hyp)
    der = (union_total_length - optimal_match_overlap) / ref_total_length
    return der</code></pre>
</details>
</dd>
<dt id="simpleder.der.build_cost_matrix"><code class="name flex">
<span>def <span class="ident">build_cost_matrix</span></span>(<span>ref, hyp)</span>
</code></dt>
<dd>
<section class="desc"><p>Build the cost matrix.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>ref</code></strong></dt>
<dd>a list of tuples for the ground truth, where each tuple is
(speaker, start, end) of type (string, float, float)</dd>
<dt><strong><code>hyp</code></strong></dt>
<dd>a list of tuples for the diarization result hypothesis, same type
as <code>ref</code></dd>
</dl>
<h2 id="returns">Returns</h2>
<p>a 2-dim numpy array, whose element (i, j) is the overlap between
<code>i</code>th reference speaker and <code>j</code>th hypothesis speaker</p></section>
<details class="source">
<summary>Source code</summary>
<pre><code class="python">def build_cost_matrix(ref, hyp):
    &#34;&#34;&#34;Build the cost matrix.

    Args:
        ref: a list of tuples for the ground truth, where each tuple is
            (speaker, start, end) of type (string, float, float)
        hyp: a list of tuples for the diarization result hypothesis, same type
            as `ref`

    Returns:
        a 2-dim numpy array, whose element (i, j) is the overlap between
            `i`th reference speaker and `j`th hypothesis speaker
    &#34;&#34;&#34;
    ref_index = build_speaker_index(ref)
    hyp_index = build_speaker_index(hyp)
    cost_matrix = np.zeros((len(ref_index), len(hyp_index)))
    for ref_element in ref:
        for hyp_element in hyp:
            i = ref_index[ref_element[0]]
            j = hyp_index[hyp_element[0]]
            cost_matrix[i, j] += compute_intersection_length(
                ref_element, hyp_element)
    return cost_matrix</code></pre>
</details>
</dd>
<dt id="simpleder.der.build_speaker_index"><code class="name flex">
<span>def <span class="ident">build_speaker_index</span></span>(<span>hyp)</span>
</code></dt>
<dd>
<section class="desc"><p>Build the index for the speakers.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>hyp</code></strong></dt>
<dd>a list of tuples, where each tuple is (speaker, start, end)
of type (string, float, float)</dd>
</dl>
<h2 id="returns">Returns</h2>
<p>a dict from speaker to integer</p></section>
<details class="source">
<summary>Source code</summary>
<pre><code class="python">def build_speaker_index(hyp):
    &#34;&#34;&#34;Build the index for the speakers.

    Args:
        hyp: a list of tuples, where each tuple is (speaker, start, end)
            of type (string, float, float)

    Returns:
        a dict from speaker to integer
    &#34;&#34;&#34;
    speaker_set = sorted({element[0] for element in hyp})
    index = {speaker: i for i, speaker in enumerate(speaker_set)}
    return index</code></pre>
</details>
</dd>
<dt id="simpleder.der.check_input"><code class="name flex">
<span>def <span class="ident">check_input</span></span>(<span>hyp)</span>
</code></dt>
<dd>
<section class="desc"><p>Check whether a hypothesis/reference is valid.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>hyp</code></strong></dt>
<dd>a list of tuples, where each tuple is (speaker, start, end)
of type (string, float, float)</dd>
</dl>
<h2 id="raises">Raises</h2>
<dl>
<dt><strong><code>TypeError</code></strong></dt>
<dd>if the type of <code>hyp</code> is incorrect</dd>
<dt><strong><code>ValueError</code></strong></dt>
<dd>if some tuple has start &gt; end; or if two tuples intersect
with each other</dd>
</dl></section>
<details class="source">
<summary>Source code</summary>
<pre><code class="python">def check_input(hyp):
    &#34;&#34;&#34;Check whether a hypothesis/reference is valid.

    Args:
        hyp: a list of tuples, where each tuple is (speaker, start, end)
            of type (string, float, float)

    Raises:
        TypeError: if the type of `hyp` is incorrect
        ValueError: if some tuple has start &gt; end; or if two tuples intersect
            with each other
    &#34;&#34;&#34;
    if not isinstance(hyp, list):
        raise TypeError(&#34;Input must be a list.&#34;)
    for element in hyp:
        if not isinstance(element, tuple):
            raise TypeError(&#34;Input must be a list of tuples.&#34;)
        if len(element) != 3:
            raise TypeError(
                &#34;Each tuple must have the elements: (speaker, start, end).&#34;)
        if not isinstance(element[0], str):
            raise TypeError(&#34;Speaker must be a string.&#34;)
        if not isinstance(element[1], float) or not isinstance(
                element[2], float):
            raise TypeError(&#34;Start and end must be float numbers.&#34;)
        if element[1] &gt; element[2]:
            raise ValueError(&#34;Start must not be larger than end.&#34;)
    num_elements = len(hyp)
    for i in range(num_elements - 1):
        for j in range(i + 1, num_elements):
            if compute_intersection_length(hyp[i], hyp[j]) &gt; 0.0:
                raise ValueError(
                    &#34;Input must not contain overlapped speech.&#34;)</code></pre>
</details>
</dd>
<dt id="simpleder.der.compute_intersection_length"><code class="name flex">
<span>def <span class="ident">compute_intersection_length</span></span>(<span>A, B)</span>
</code></dt>
<dd>
<section class="desc"><p>Compute the intersection length of two tuples.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>A</code></strong></dt>
<dd>a (speaker, start, end) tuple of type (string, float, float)</dd>
<dt><strong><code>B</code></strong></dt>
<dd>a (speaker, start, end) tuple of type (string, float, float)</dd>
</dl>
<h2 id="returns">Returns</h2>
<p>a float number of the intersection between <code>A</code> and <code>B</code></p></section>
<details class="source">
<summary>Source code</summary>
<pre><code class="python">def compute_intersection_length(A, B):
    &#34;&#34;&#34;Compute the intersection length of two tuples.

    Args:
        A: a (speaker, start, end) tuple of type (string, float, float)
        B: a (speaker, start, end) tuple of type (string, float, float)

    Returns:
        a float number of the intersection between `A` and `B`
    &#34;&#34;&#34;
    max_start = max(A[1], B[1])
    min_end = min(A[2], B[2])
    return max(0.0, min_end - max_start)</code></pre>
</details>
</dd>
<dt id="simpleder.der.compute_merged_total_length"><code class="name flex">
<span>def <span class="ident">compute_merged_total_length</span></span>(<span>ref, hyp)</span>
</code></dt>
<dd>
<section class="desc"><p>Compute the total length of the union of reference and hypothesis.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>ref</code></strong></dt>
<dd>a list of tuples for the ground truth, where each tuple is
(speaker, start, end) of type (string, float, float)</dd>
<dt><strong><code>hyp</code></strong></dt>
<dd>a list of tuples for the diarization result hypothesis, same type
as <code>ref</code></dd>
</dl>
<h2 id="returns">Returns</h2>
<p>a float number for the union total length</p></section>
<details class="source">
<summary>Source code</summary>
<pre><code class="python">def compute_merged_total_length(ref, hyp):
    &#34;&#34;&#34;Compute the total length of the union of reference and hypothesis.

    Args:
        ref: a list of tuples for the ground truth, where each tuple is
            (speaker, start, end) of type (string, float, float)
        hyp: a list of tuples for the diarization result hypothesis, same type
            as `ref`

    Returns:
        a float number for the union total length
    &#34;&#34;&#34;
    # Remove speaker label and merge.
    merged = [(element[1], element[2]) for element in (ref + hyp)]
    # Sort by start.
    merged = sorted(merged, key=lambda element: element[0])
    num_elements = len(merged)
    for i in reversed(range(num_elements - 1)):
        if merged[i][1] &gt;= merged[i + 1][0]:
            max_end = max(merged[i][1], merged[i + 1][1])
            merged[i] = (merged[i][0], max_end)
            del merged[i + 1]
    total_length = 0.0
    for element in merged:
        total_length += element[1] - element[0]
    return total_length</code></pre>
</details>
</dd>
<dt id="simpleder.der.compute_total_length"><code class="name flex">
<span>def <span class="ident">compute_total_length</span></span>(<span>hyp)</span>
</code></dt>
<dd>
<section class="desc"><p>Compute total length of a hypothesis/reference.</p>
<h2 id="args">Args</h2>
<dl>
<dt><strong><code>hyp</code></strong></dt>
<dd>a list of tuples, where each tuple is (speaker, start, end)
of type (string, float, float)</dd>
</dl>
<h2 id="returns">Returns</h2>
<p>a float number for the total length</p></section>
<details class="source">
<summary>Source code</summary>
<pre><code class="python">def compute_total_length(hyp):
    &#34;&#34;&#34;Compute total length of a hypothesis/reference.

    Args:
        hyp: a list of tuples, where each tuple is (speaker, start, end)
            of type (string, float, float)

    Returns:
        a float number for the total length
    &#34;&#34;&#34;
    total_length = 0.0
    for element in hyp:
        total_length += element[2] - element[1]
    return total_length</code></pre>
</details>
</dd>
</dl>
</section>
<section>
</section>
</article>
<nav id="sidebar">
<h1>Index</h1>
<div class="toc">
<ul></ul>
</div>
<ul id="index">
<li><h3>Super-module</h3>
<ul>
<li><code><a title="simpleder" href="index.html">simpleder</a></code></li>
</ul>
</li>
<li><h3><a href="#header-functions">Functions</a></h3>
<ul class="">
<li><code><a title="simpleder.der.DER" href="#simpleder.der.DER">DER</a></code></li>
<li><code><a title="simpleder.der.build_cost_matrix" href="#simpleder.der.build_cost_matrix">build_cost_matrix</a></code></li>
<li><code><a title="simpleder.der.build_speaker_index" href="#simpleder.der.build_speaker_index">build_speaker_index</a></code></li>
<li><code><a title="simpleder.der.check_input" href="#simpleder.der.check_input">check_input</a></code></li>
<li><code><a title="simpleder.der.compute_intersection_length" href="#simpleder.der.compute_intersection_length">compute_intersection_length</a></code></li>
<li><code><a title="simpleder.der.compute_merged_total_length" href="#simpleder.der.compute_merged_total_length">compute_merged_total_length</a></code></li>
<li><code><a title="simpleder.der.compute_total_length" href="#simpleder.der.compute_total_length">compute_total_length</a></code></li>
</ul>
</li>
</ul>
</nav>
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